Paper Citation Record · LEDGER

CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2312.10527.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2312.10527 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:10:03.578002Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T19:56:11.117235Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ed299560-a8b0-43dc-93ec-4d989a066c45 · inbound

Consistency Training with Physical Constraints cites this paper.

Consistency Training with Physical Constraints CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T12:10:03.578002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf07d7ac-8bc8-4052-bf4f-2c0909c450ee · inbound

Machine learning for modelling unstructured grid data in computational physics: a review cites this paper.

Machine learning for modelling unstructured grid data in computational physics: a review CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T21:49:40.382453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0277a39-24b0-47fc-bdef-9ca00cecdb43 · inbound

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series cites this paper.

Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T19:56:11.122377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 51622383-5496-44f7-8aa9-73f7bc5428b7 · inbound

Stabilizing Physics-Informed Consistency Models via Structure-Preserving Training cites this paper.

Stabilizing Physics-Informed Consistency Models via Structure-Preserving Training CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problems

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T03:04:32.093876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.